Approximation and Intractability Results for the Maximum Cut Problem and Its Variants
IEEE Transactions on Computers
A combinatorial design approach to MAXCUT
Proceedings of the seventh international conference on Random structures and algorithms
The size of the largest bipartite subgraphs
Discrete Mathematics
Journal of Computer and System Sciences - Special issue on the fourteenth annual IEE conference on computational complexity
On the existence of subexponential parameterized algorithms
Journal of Computer and System Sciences - Special issue on Parameterized computation and complexity
Maximizing Quadratic Programs: Extending Grothendieck's Inequality
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Parameterizing above or below guaranteed values
Journal of Computer and System Sciences
On problems without polynomial kernels
Journal of Computer and System Sciences
Note on maximal bisection above tight lower bound
Information Processing Letters
Parameterized Complexity
Bisections above tight lower bounds
WG'12 Proceedings of the 38th international conference on Graph-Theoretic Concepts in Computer Science
Maximum balanced subgraph problem parameterized above lower bound
Theoretical Computer Science
Satisfying more than half of a system of linear equations over GF(2): A multivariate approach
Journal of Computer and System Sciences
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We study the boundary of tractability for the Max-Cut problem in graphs. Our main result shows that Max-Cut above the Edwards-Erdős bound is fixed-parameter tractable: we give an algorithm that for any connected graph with n vertices and m edges finds a cut of size $$ \frac{m}{2} + \frac{n-1}{4} + k $$ in time 2O(k)·n4, or decides that no such cut exists. This answers a long-standing open question from parameterized complexity that has been posed a number of times over the past 15 years. Our algorithm is asymptotically optimal, under the Exponential Time Hypothesis, and is strengthened by a polynomial-time computable kernel of polynomial size.